Technical Note—Managing Nonperishable Inventories with Learning About Demand Arrival Rate Through Stockout Times
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 602-609 |
Journal / Publication | Operations Research |
Volume | 63 |
Issue number | 3 |
Online published | 13 May 2015 |
Publication status | Published - May 2015 |
Link(s)
Abstract
We study a periodic review inventory model with a nonperishable product over an infinite planning horizon. The demand for the nonperishable product arrives according to a Poisson process. Lost sales are unobservable but the stockout times are observable. We formulate the problem as a dynamic programming model with learning on arrival rate according to stockout times and further simplify it by using unnormalized probabilities. We then compare the system performance with those under other two information scenarios where lost sales are observable or both lost sales and stockout times are unobservable. We show that the optimal inventory order-up-to level with observable stockout times is larger than the one with observable lost sales. We also show that more information improves the system performance.
Research Area(s)
- information updating, inventory management, Bayesian statistics, nonperishable products
Citation Format(s)
Technical Note—Managing Nonperishable Inventories with Learning About Demand Arrival Rate Through Stockout Times. / Bensoussan, Alain; Guo, Pengfei.
In: Operations Research, Vol. 63, No. 3, 05.2015, p. 602-609.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review